Prioritizing Clinically Important Outcomes Using Hierarchical Win Ratio
Clinical trials often use composite outcomes, but conventional analysis methods have limitations in accurately reflecting clinical reality. Hierarchical outcomes offer flexibility by defining a hierarchy of events based on importance. Analyzing trials using hierarchical outcomes involves comparing p
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System Models in Software Engineering: A Comprehensive Overview
System models play a crucial role in software engineering, aiding in understanding system functionality and communicating with customers. They include context models, behavioural models, data models, object models, and more, each offering unique perspectives on the system. Different types of system
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Clustering Algorithms: K-means and Hierarchical Clustering
Explore the concepts of clustering and retrieval in machine learning, focusing on K-means and Hierarchical Clustering algorithms. Learn how clustering assigns labels to data points based on similarities, facilitates data organization without labels, and enables trend discovery and predictions throug
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Models of Teaching for Effective Learning
Models of teaching serve as instructional designs to facilitate students in acquiring knowledge, skills, and values by creating specific learning environments. Bruce Joyce and Marsha Weil classified teaching models into four families: Information Processing Models, Personal Models, Social Interactio
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Significance of Models in Agricultural Geography
Models play a crucial role in various disciplines, including agricultural geography, by offering a simplified and hypothetical representation of complex phenomena. When used correctly, models help in understanding reality and empirical investigations, but misuse can lead to dangerous outcomes. Longm
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Design and Evaluation of Hierarchical Rings with Deflection Routing
This research explores the implementation of Hierarchical Rings with Deflection (HiRD) routing as a solution to the performance and energy inefficiencies found in traditional hierarchical ring designs. HiRD guarantees livelock freedom and efficient delivery while simplifying the network structure by
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Creating Second Hierarchical Data Table in Windchill PDMLink
Learn how to set up a second hierarchical data table in Windchill PDMLink by selecting rows from the first table to view and interact with related objects in a structured manner. The process involves customization and user actions within the tables to manage parts and documents efficiently.
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Cross-Classified Models in Multilevel Modelling
Cross-classified models in multilevel modelling involve non-hierarchical data structures where entities are classified within multiple categories. These models extend traditional nested multilevel models by accounting for complex relationships among data levels. Professor William Browne from the Uni
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Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification
A study conducted by Zheng Li, Ying Wei, Yu Zhang, and Qiang Yang from the Hong Kong University of Science and Technology on utilizing a Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification. The research focuses on sentiment classification testing data of books, training
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Data Summarization with Hierarchical Taxonomy: Motivations and Examples
The research discusses the use of Hierarchical DAGs in summarizing data with a focus on disease ontology and animal diseases. It explores how general concepts can summarize specific items and their relationships. The study also presents motivated examples of popular papers summarization in SIGMOD, s
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Classifying Entities into an Incomplete Ontology: Exploratory EM Approach
The research discusses methods for hierarchical classification of entities into incomplete ontologies. It explores the challenges of evolving web-scale datasets and the need for classifying entities in an incomplete ontology structure. The Hierarchical Exploratory EM model is detailed, providing ins
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Denoising-Oriented Deep Hierarchical Reinforcement Learning for Next-basket Recommendation
This research paper presents a novel approach, HRL4Ba, for Next-basket Recommendation (NBR) by addressing the challenge of guiding recommendations based on historical baskets that may contain noise products. The proposed Hierarchical Reinforcement Learning framework incorporates dynamic context mode
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Hierarchical Semi-Supervised Classification with Incomplete Class Hierarchies
This research explores the challenges and solutions in semi-supervised entity classification within incomplete class hierarchies. It addresses issues related to food, animals, vegetables, mammals, reptiles, and fruits, presenting an optimized divide-and-conquer strategy. The goal is to achieve semi-
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Enhanced Energy Storage Model Proposal for Li-ion and Flow Batteries
Exploring similarities and differences between Li-ion and Flow Batteries, the workgroup aims to structure models that build on commonalities without restricting a specific technology. Participants express interest in expanding the models to deeper hierarchical levels. The proposed models cover diffe
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Building Hierarchical Ratings Model without Alternatives Listed
Learn to build a hierarchical ratings model with 4 criteria, including subcriteria for Comfort, using a step-by-step approach. Explore how to select covering criteria, create performance scales, add and rate alternatives, and prioritize rating intensities for effective evaluation. Streamline your ra
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Efficient and Effective Duplicate Detection in Hierarchical Data
This study explores the efficient and effective detection of duplicates in hierarchical data, focusing on fuzzy duplicates and hierarchical relationships in XML. It discusses the current and proposed systems, including the use of Bayesian networks for similarity computations. The methods involve vec
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Graph Summarization on Hierarchical DAGs
Explore top-k graph summarization techniques on Hierarchical Directed Acyclic Graphs (DAGs) like Disease Ontology, ImageNet, and Wikipedia Categories. Understand motivations for summarization, related works, and the kDAG-Problem. Discover algorithms, experiments, and conclusions for efficient graph
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Hierarchical vs. Non-Hierarchical Models in Computer Graphics
Dive into the concepts of hierarchical and non-hierarchical modeling in computer graphics. Explore how hierarchical models represent complex objects with explicit sub-part dependencies, while non-hierarchical models treat objects independently. Understand the benefits and challenges of each approach
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Utilizing Bayesian Hierarchical Model for Clinical Trial Quality Design
Explore how a Bayesian Hierarchical Model can be leveraged to design quality into clinical trials and ensure compliance with ICH E6 R2 Quality Tolerance Limits. Learn about the Risk-Based approach, Quality Tolerance Limits methodology, and the application of Bayesian modeling for early phase studies
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Hierarchical Body Modeling in OpenGL Homework 3
Explore the concepts of hierarchical body modeling in OpenGL Homework 3 by creating body part hierarchies, recording transformation matrices, and understanding the hierarchy structures. The homework focuses on building hierarchies for body parts like thighs and shanks, applying transformations, and
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Machine Learning Approach for Hierarchical Classification of Transposable Elements
This study presents a machine learning approach for the hierarchical classification of transposable elements (TEs) based on pre-annotated DNA sequences. The research includes data collection, feature extraction using k-mers, and classification approaches. Proper categorization of TEs is crucial for
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Risk Adjustment Hierarchical Condition Categories
The Centers for Medicare and Medicaid Services (CMS) introduced the Hierarchical Condition Categories (HCC) coding payment model in 2004 for Medicare Advantage and Prescription Drug Plans. This model adjusts payments based on enrollees' demographics and health status, using 70 HCC categories correla
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Particle-laden Turbulence in a Radiation Environment: Efficient Linear Solver
This research focuses on developing a parallel linear solver using hierarchical matrix techniques to solve particle-laden turbulence problems in radiation environments. Motivations include tackling large linear systems from various applications and leveraging heterogeneous machine architectures. The
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Improved Hierarchical Word Sequence Language Model Using Word Association
This research presents an enhanced hierarchical word sequence language model leveraging word association techniques. It explores the motivation behind the model, smoothing techniques for data sparsity, and the basic idea of the proposed approach, focusing on patterns and word generation. The propose
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Hierarchical Sensitivity
Sensitivity studies analyze how the priorities of alternatives change as criteria priorities vary. Explore graphical sensitivity techniques and interpretations to make informed decisions in hierarchical structures.
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Hierarchical Clustering
- Hierarchical clustering is a versatile technique in data mining that creates a hierarchical decomposition of objects based on similarity or distance measures. This clustering method offers insights into data relationships through dendrograms, allowing for the identification of outliers and the exp
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Lagged Dependent Variable Models in Regression Analysis
Lagged dependent variables are utilized in various regression models such as distributed lag models, partial-adjustment models, models with expectations, and models with serially correlated residuals. By incorporating lagged dependent variables, researchers can analyze the impact of past values on t
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Computer Simulation Models Classification
Computer simulation models are classified based on various characteristics such as static or dynamic, deterministic or stochastic, and discrete or continuous. Static models represent systems at a specific point in time, while dynamic models depict changes over time. Deterministic models involve no r
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Hierarchical Model for Object-Oriented Design Quality Assessment
This article introduces a hierarchical model for assessing the quality of object-oriented design in software engineering. Starting with an overview of software quality and its importance, it delves into previous work on quality models and metrics, highlighting the need for improvement. The motivatio
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Database Management Systems: Understanding Hierarchical Models in Databases
Explore the fundamentals of databases storing information, including records, connections, and searching methods. Delve into the hierarchical model exemplified by department and employee data, illustrating how to locate and retrieve specific information efficiently within a structure. Discover the s
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Robot Behavior Planning and Control Architectures
Explore hierarchical and state-based architectures for robot behavior planning and control, including motivation, approaches, frameworks, and components. Learn about the State Controller Library (SCL) and its platform-independent C++ framework for implementing finite state machines and hierarchical
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Hierarchical Modulation for Improved WLAN Connectivity
Explore the innovative Hierarchical Modulation (HM) proposal by Samsung for IEEE 802.11, aiming to enhance reliability and reduce latency in WLAN connectivity under interference scenarios. The concept involves modulating high and low priority data streams into a single symbol stream, providing bette
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Hierarchical Approach to Signal Processing and Control in SKA Elements
Explore the hierarchical architecture of the Central Signal Processor Local Monitor and Control system in SKA elements, highlighting the organization, communication, and coordination of sub-elements for effective monitoring and control. Learn about the responsibilities, communication protocols, and
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Verilog Primer: Hierarchical Design and Logic Modules
Learn about hierarchical design and logic modules in Verilog. Understand how to create and structure complex designs for better readability and reusability. Follow along with examples showcasing the design process step by step.
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Verilog Primer: Hierarchical Design Concepts and Examples
Explore the fundamentals of hierarchical design in Verilog through basic constructs, combinatorial logic, and sequential logic. Learn how to create modular and reusable designs by dividing them into blocks and modules. Dive into examples like the 4-bit Equality design to understand the practical app
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Capsule Network for Multi-Label Image Classification Study
Explore a Capsule Network for Hierarchical Multi-Label Image Classification through a detailed analysis of classification approaches, hierarchical structure, and CapsNet models. This study delves into Class Taxonomy, Hierarchical Classifiers, CNN-Based Classifiers, and Capsule Networks' innovative f
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Hierarchical Generalized Linear Models for Behavioral Health Readmission Rates
Dr. Allen Hom, a Senior Research Analyst at Optum, specializes in advanced statistics and behavioral health analytics. He has significant experience in SAS programming and has conducted research on hierarchical generalized linear models to adjust for patient clustering effects in hospital readmissio
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Task and Motion Planning in Robotics: A Hierarchical Approach
Explore the challenges and strategies of creating a general agent capable of robustly performing diverse tasks in varied environments through a hierarchical task and motion planning approach. Delve into the history of deep reinforcement learning and the fusion of symbolic task planning with low-leve
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Understanding Database Modeling: Hierarchical, Network, and Entity Relationship Models
Explore different database modeling concepts including hierarchical, network, and entity-relationship models. Learn how data is organized, relationships are established, and how entity-relationship diagrams visually represent database structures.
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Understanding Data Modeling: Entity Relationship, Relational, Hierarchical, and Network Models
Explore the world of data modeling through Entity Relationship, Relational, Hierarchical, and Network Models. Learn about entities, attributes, relationships, tables, hierarchies, and schema design in a database. Dive into the basics of data organization and structure for effective database manageme
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